Type
ArticleKAUST Department
Electrical Engineering ProgramComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Sensors Lab
Date
2009-09Permanent link to this record
http://hdl.handle.net/10754/561423
Metadata
Show full item recordAbstract
Maximum-likelihood (ML) detection for higher order multiple-input-multiple-output (MIMO) systems faces a major challenge in computational complexity. This limits the practicality of these systems from an implementation point of view, particularly for mobile battery-operated devices. In this paper, we propose a modified approach for MIMO detection, which takes advantage of the quadratic-amplitude modulation (QAM) constellation structure to accelerate the detection procedure. This approach achieves low-power operation by extending the minimum number of paths and reducing the number of required computations for each path extension, which results in an order-of-magnitude reduction in computations in comparison with existing algorithms. This paper also describes the very-large-scale integration (VLSI) design of the low-power path metric computation unit. The approach is applied to a 4 × 4, 64-QAM MIMO detector system. Results show negligible performance degradation compared with conventional algorithms while reducing the complexity by more than 50%. © 2009 IEEE.Citation
Mondal, S., Eltawil, A. M., & Salama, K. N. (2009). Architectural Optimizations for Low-Power $K$-Best MIMO Decoders. IEEE Transactions on Vehicular Technology, 58(7), 3145–3153. doi:10.1109/tvt.2009.2017548Sponsors
Manuscript received January 29, 2009. First published March 16, 2009; current version published August 14, 2009. This work was supported in part by the Center for Automation Technologies and Systems under a block grant from the New York State Foundation for Science, Technology, and Innovation and Grant 2006-IJ-CX-K044 from the National Institute of Justice under the Department of Justice. The review of this paper was coordinated by Dr. H. H. Nguyen.ae974a485f413a2113503eed53cd6c53
10.1109/TVT.2009.2017548